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IEEE NSS 2003 Performance of the Relational Grid Monitoring Architecture (R-GMA) CMS data challenges. The nature of the problem. What is GMA ? And what.

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Presentation on theme: "IEEE NSS 2003 Performance of the Relational Grid Monitoring Architecture (R-GMA) CMS data challenges. The nature of the problem. What is GMA ? And what."— Presentation transcript:

1 IEEE NSS 2003 Performance of the Relational Grid Monitoring Architecture (R-GMA) CMS data challenges. The nature of the problem. What is GMA ? And what is R-GMA ? Performance test description Performance test results Conclusions

2 IEEE NSS 2003 The Nature of the problem As part of the preparations for data taking CMS is performing DATA CHALLENGES. Large number of simulated events to optimise detectors and prepare software Enormous processing requirements BUT each event is independent of all the others each event can be generated on a machine without any interaction with any other

3 IEEE NSS 2003 The local solution Work split between farms. How to handle the book-keeping ? a data-base automatically updated Implemented via a job wrapper BOSS Output to and is intercepted and the information is recorded in a mySQL production database. Event generation and job accounting decoupled

4 IEEE NSS 2003 The local solution (schematic) Database Machine Submission Machine UI Worker Node (WN) WN

5 IEEE NSS 2003 The grid solution (schematic) Database Machine Submission Machine UI

6 IEEE NSS 2003 Grid Monitoring Architecture (GMA) of the GGF Producer Consumer Registry (Directory services) register producer locate producer address of producer data Ask for data

7 IEEE NSS 2003 R-GMA (Relational GMA) Developed for E(uropean) D(ata) G(rid) Extends the GMA in two important ways 1.Introduces a time stamp on the data. 2.A relational implementation 3.Hides the registry behind the API Can be used for information and monitoring Each V irtual O rganisation appears to have one RDBMS

8 IEEE NSS 2003 The syntax of R-GMA The user interface to R-GMA is via SQL statements (not all SQL statements and structures are supported) Information is advertised via a table create Information is published via insert Information is read via select … from table The first read request registers the consumer as interested in this data. Relational queries are supported NOTE : sql is the interface – it should not be supposed an actual database lies behind it.

9 IEEE NSS 2003 Fit between R-GMA and BOSS R-GMA can be dropped into the framework with very little disruption 1.Set up calls for mySQL are replaced by those for R-GMA producers 2.An archiver (joint consumer/producer) runs on a single machine which collects the data from all the running jobs and writes it to a local database (and possible republishes it). The data can then be queried either by direct mySQL calls or via R-GMA consumer (a distributed database has been created)

10 IEEE NSS 2003 Database BOSS LAN Connection R-GMA WAN Connection Fit between R-GMA and BOSS (i)

11 IEEE NSS 2003 R-GMA Measurements The architecture of GMA clearly provides a putative solution to the wide area monitoring problem. BUT Does a specific implementation provide a practical solution Before entrusting CMS production to R-GMA, we must be confident that it will perform. What load will it fail at and why ?

12 IEEE NSS 2003 Message time distribution from 44 jobs 35 chars.

13 IEEE NSS 2003 Simulation of a CMS job Multi-threaded job each thread produces messages. Length 35 chars, suitable distribution. Threads starting time distribution can be altered. One machine delivers the R-GMA load of a farm. R-GMA servlet R-GMA consumer

14 IEEE NSS 2003 Simulation of the CMS Grid One machine per grid cluster providing loads of greater than the cluster R-GMA consumer R-GMA servlet R-GMA servlet R-GMA servlet R-GMA servlet

15 IEEE NSS 2003 Current status R-GMA can survive loads of around 20% of the current CMS requirements and does provides a grid method for monitoring. An overload of a factor 2 jobs causes problems after about five minutes running. We believe these instabilities are soluble. When production starts in earnest we will compare reality with our model.


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